Elasticsearch is a search engine that is based on the Apache Lucene project and library. Elasticsearch provides NoSQL features plus some advantages and acts like a big database. Also, Elasticsearch provides distributed, multitenant-capable full-text search over the HTTP protocol and web interface.
Elasticsearch History
Elasticsearch is created by Shay Bannon in order to create a scalable search solution by using previous experience. The first version of the Elasticsearch is released in February 2010. Elasticsearch gained popularity and as a result, Elastic NV was founded in 2012 to provide commercial services and products by using Elasticsearch. During 2014 Elastic NY company raised about $174 million. In March 2015 the company changed its name to “Elastic”. In June Elastic company is valued at about 3 billion dollars.
Elasticsearch Features
What makes Elasticsearch so popular and useful is its advenced andunique fetures.
Distributed: Elasticsearch is distributed which means data is divided into multiple shards/files and same data piece can be stored single or multiple shards for redundancy.
High Performance : Elasticsearch provides high performance for its operations.
Store and Search Different Data Types: Elasticsearch is designed to store and search different data or document types like text, binary, image etc.
Real-time Search: Even not exact real-time elasticsearch provides almost real-time operations for add, update, search actions.
Rich Toolset : Elasticsarch provides and integrated with useful tools which make elasticsearc more powerful. Especially the ELK stack is very popular where Elasticsearch is used store and query data, Logstash is used to collect, parse data and log, Kibana is used to provide GUI and web interface to list, search and manage the data/log.
Lucene Based: Elasticsearch uses the Apache Lucene project and library as base which is very stable and fast NoSQL engine.
HTTP API/Interface: Elasticsearch provides HTTP API or interface in order to manage, add, update, delete and query data. This api support makes to use Elasticsearch from different devices and platform easily without diving into details of different platforms and programming languages.
Library and SDK : Even elasticsearch provides HTTP API/Interface it also supports different programming languages and frameworks like Java, JavaScript, Ruby, Go, .NET, PHP, Perl, Python, Rust.
As Managed Service : Elastic also provides the elasticsearch as SaaS solution over different cloud providers like Amazon Web Services, Google Cloud Platform, Azure. This makes elasticsearch very easy to use project based with high resources.
Elasticsearch Advantages
Elasticsearch has a lot of advantages with its features and popularity below we will list some of the biggest advantages of the elasticsearch.
- Elasticsearch can be installed easily with different methods like Binary, Docker container, cloud.
- Elasticsearch can be used all different platforms because of its rich support for API and REST/JSON based HTTP interface.
- Elasticsearch is very fast with its shard, multitenant, and distributed architecture.
- Elasticsearch is reliable by using multiple shards for the same data piece and distributed this data into different hosts over the network.
- High-level support is another big advantage of the elasticsearch because of its community and enterprise-level services.
- The complete toolset is another advantage of the elasticsearch where different tools complete the creation of a required environment for big data, distributed search and storage, etc.